Principle:Mistralai Client python Function Dispatch
| Knowledge Sources | |
|---|---|
| Domains | Function_Calling, Design_Pattern |
| Last Updated | 2026-02-15 14:00 GMT |
Overview
A dispatch pattern that routes model-requested function calls to actual Python function implementations and collects their results.
Description
Function Dispatch is the user-implemented step that bridges the model's tool call request with actual function execution. After parsing ToolCall objects from the model's response, the application must map function names to callable Python functions, deserialize the arguments, invoke the function, and serialize the result as a string. This is typically implemented with a name-to-function dictionary lookup.
Usage
Use this principle after parsing tool calls from a model response. Implement a dispatch mechanism that maps function names to their implementations and handles argument conversion and error handling.
Theoretical Basis
Function dispatch follows the command pattern:
- Maintain a registry mapping function names to callables
- Look up the requested function by name
- Deserialize JSON arguments to Python objects
- Invoke the function with the parsed arguments
- Serialize the return value as a string for the model
# Pseudocode for function dispatch
registry = {"get_weather": get_weather_fn, "search_db": search_fn}
for tool_call in tool_calls:
fn = registry[tool_call.function.name]
args = json.loads(tool_call.function.arguments)
result = fn(**args)
results.append((tool_call.id, str(result)))